System and method to anonymously test for proximity of mobile users without revealing individual phase space coordinates

• US 20040198373A1
• Filed: 12/03/2002
• Published: 10/07/2004
• Est. Priority Date: 12/03/2002
• Status: Active Grant

• Current Assignee: Lenovo PC International Limited (Lenovo Group Ltd.)
• Original Assignee: Lenovo Singapore Pte Limited (Lenovo Group Ltd.)
• Inventors: Myllymaki, Jussi Petri, Kaufman, James Harvey, Ford, Daniel Alexander
• Granted Patent: US 6,823,190 B2
• Time in Patent Office: Days
• US Class Current: 455/456.1
• CPC Class Codes: G08B 2001/085 Partner search devices
• CPC Class Codes: H04M 2242/30 Determination of the location of a subscriber
• CPC Class Codes: H04M 3/42229 Personal communication services, i.e. services related to one subscriber independent of his terminal and/or location diverting calls from one subscriber to another subscriber, i.e. two different subscriptions H04M3/54; selecting arrangements in intelligent networks H04Q3/005
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 8/18 Processing of user or subscriber data, e.g. subscribed services, user preferences or user profiles; Transfer of user or subscriber data

Abstract

Described is a way for computing proximity (location-based proximity or preference-based proximity) between mobile wireless subscribers (who use different services) without either divulging their location/preference to the other (preservation of privacy). Privacy is kept by providing location/preference information in steps, along with an evaluation function. The services receive partial results and then locally compute the final result, or proximity. The term proximity includes not just physical proximity but also multi-dimensional data such as preference profiles and vectors (e.g., an affinity for baseball, apple pie, and ballroom dancing).

Claims

1. A method for assisting a first and second tracking service in anonymizing preference data associated with a first and second user in a phase space, said first and second tracking service tracking preferences of said first and second user respectively, said preference data being defined by one or more parameters, said method comprising the steps of:

a. receiving a request for function evaluation from each tracking service, said request identifying a parameter to be transmitted and a corresponding function to be used for evaluating said identified parameter;

b. transmitting a confirmation to each tracking service indicating transmission of said identified parameter is expected;

c. receiving said identified parameter from each tracking service;

d. evaluating said corresponding function based on said received parameter from each tracking service;

e. transmitting said evaluated result to each tracking service; and

wherein steps a through e are repeated for each additional parameter required to define preference data and corresponding function such that each of said service'"'"'s receives function evaluated results for each parameter separately and utilizes such evaluated results to locally estimate proximity between said first and second user in said phase space without revealing their preference data.

2. A method as per claim 1, wherein communications with said tracking service is done via the hypertext transfer protocol (HTTP).

3. A method as per claim 1, wherein said parameters are Euclidean coordinates.

4. A method as per claim 1, wherein said parameters are scalar measures of said preference data.

5. A method as per claim 1, wherein said parameters are vector measures of said preference data.

6. An article of manufacture comprising a computer usable medium having computer readable program code embodied therein for assisting a first and second tracking service in anonymizing preference data associated with a first and second user in a phase space, said first and second tracking service tracking preferences of said first and second user respectively, said preference data being defined by one or more parameters, said method comprising the steps of:

a. computer readable program code aiding in receiving a request for function evaluation from each tracking service, said request identifying a parameter to be transmitted and a corresponding function to be used for evaluating said identified parameter;

b. computer readable program code aiding in transmitting a confirmation to each tracking service indicating transmission of said identified parameter is expected;

c. computer readable program code aiding in receiving said identified parameter from each tracking service;

d. computer readable program code evaluating said corresponding function based on said received parameter from each tracking service;

e. computer readable program code aiding in transmitting said evaluated result to each tracking service; and

wherein computer readable program code of steps a through e are repeated for each additional parameter required to define preference data and corresponding function such that each of said service'"'"'s receives function evaluated results for each parameter separately and utilizes such evaluated results to locally estimate proximity between said first and second user in said phase space without revealing their preference data.

7. A method for anonymous proximity detection between a first and second mobile user, said first and second mobile users being tracked by a first and second location tracking service (LTS) respectively, said method as implemented by each LTS comprising the steps of:

a. transmitting, to a third party, a first location coordinate along with a corresponding first function to evaluate;

b. receiving a first result from said third party, said first result based upon an evaluation of said first function with said first location coordinate;

c. transmitting, to said third party, a second location coordinate along with a second corresponding function to evaluate;

d. receiving a second result from said third party, said second result based upon an evaluation of second function with said second location coordinate; and

e. computing a measure of distance based upon said received first and second results, said computed distance providing each user with an indication of proximity with respect to the other user.

8. A method as per claim 7, wherein said third party is a non-trusted third party.

9. A method as per claim 7, wherein communications between said users and said LTS is using the hypertext transfer protocol (HTTP).

10. A method as per claim 7, wherein said computed distance is measured against a threshold to determine said indication of proximity.

11. A method as per claim 7, wherein said step of computing distance is implemented locally in a mobile device associated with said mobile users.

12. A method as per claim 11, wherein said distance is computed using a Java Virtual Machine embedded in said mobile device.

13. An anonymous function evaluation service (AFES) comprising:

a. an interface communicating with various tracking services or wireless service providers (WSPs) and receiving parameters and corresponding functions, said parameters associated with one or more users;

b. a task list storing said functions to be evaluated on received data;

c. a data cache storing said received parameters to be processed;

d. a function evaluation engine evaluating mathematical function(s) on parameters; and

e. a task manager operatively linked with said task list, data cache, and function evaluation engine, said task manager;

(i) receiving parameters and corresponding functions from said interface;

(ii) sending said functions and parameters to task list and data cache respectively;

(iii) retrieving said functions from data cache; and

(iv) communicating with function evaluation engine and sending results of said function evaluation engine back to said interface for forwarding values to requesting services.

14. An anonymous function evaluation service as per claim 13, wherein said parameters are Euclidian coordinates.

15. An anonymous function evaluation service as per claim 14, wherein said Euclidean coordinates are in a floating point format.

16. An anonymous function evaluation service as per claim 13, wherein said parameters are scalar measures of preferences associated with users.

17. An anonymous function evaluation service as per claim 13, wherein said parameters are vector measures of preferences associated with users.

18. An anonymous function evaluation service as per claim 13, wherein said interface communicates via the hypertext transfer protocol (HTTP).

19. An anonymous function evaluation service as per claim 13, wherein said AFES is a non-trusted third party.

20. An anonymous function evaluation service as per claim 13, wherein said task manager performs validity checks on said parameters, evaluation functions, and any identifying keys.